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• Faculty development on artificial intelligence improves incorporation of complex assessment questions in medical physiology
  Background: Physiological content is difficult to master due to the interrelated nature of organ systems. This is compounded in medical school programs by shorter time frames for content mastery and higher stakes exams. Medical licensure exams incorporate comp…
  crossref Alex Shefflette, Cynthia Metz, Michael Metz 2026-05-12T19:52:42Z 置信度 0.70
• Interpretable dynamic quantitative vascular morphometry features using SHAP for anti-angiogenic therapy response prediction.
  Anti-angiogenic therapy benefits vary, with response rates of 40 to 70%, highlighting the need for early biomarkers to identify responders. We developed an automated machine learning framework that uses delta quantitative vascular morphometry features from sta…
  pubmed Hu K, Cai Q, Xu J, Ai S 等 2026 Jul 24 置信度 0.82
• Fundus image analysis of retinitis pigmentosa using artificial intelligence.
  Retinitis pigmentosa (RP) is a group of inherited retinal diseases that are caused by genetic defects that lead to progressive photoreceptor loss and eventual blindness. Early diagnosis would be helpful for effective management of the disease; however, many pa…
  pubmed Ubukata S, Masayoshi K, Katada Y, Yang L 等 2026 置信度 0.82
• A 3-dimensional Resnet model for assessment of drug efficacy in 3D cancer models using optical coherence tomography.
  Ninety percent of drugs fail during clinical trials, mainly due to lack of clinical efficacy. Recent developments in in vitro models such as 3D tumor heterospheroids have led to improvements in failure rates, but the relative lack of standardized evaluation me…
  pubmed Untracht GR, Kaminski J, Guldenring E, Nielsen BS 等 2026 置信度 0.82
• An Interpretable Machine Learning Model for Continuous Prediction of Acute Kidney Injury in Critically Ill Patients With Atrial Fibrillation.
  The occurrence of acute kidney injury (AKI) in hospitalized patients with atrial fibrillation (AF) significantly increases the mortality risk. Currently, effective tools for early identification and dynamic predictive models remain lacking for this high-risk p…
  pubmed Liu W, Zhao F, Qin H, He J 2026 Jul 24 置信度 0.82
• Machine learning versus conventional grading systems for prognostication in aneurysmal subarachnoid hemorrhage: a systematic review and meta-analysis.
  Accurate prognostication after aneurysmal subarachnoid hemorrhage (aSAH) remains challenging. Conventional clinical and radiological grading systems, including the World Federation of Neurosurgical Societies (WFNS), Hunt-Hess, and Fisher scales, are widely use…
  pubmed Ogolo D, Akwada O, Ajare E, Opara B 等 2026 Jul 24 置信度 0.82
• Development and validation of a machine learning-based hierarchical classification model for predicting the early therapeutic response to initial (131)I therapy in papillary thyroid carcinoma.
  Personalized tools for accurately predicting papillary thyroid carcinoma (PTC) patients' response to initial 131 I therapy are lacking. This study aimed to develop a machine learning (ML) model for prediction of 6-12 month therapeutic response after thera…
  pubmed Tang Z, Wang Z, Pang H 2026 Jul 24 置信度 0.82
• A Framework for Predicting Neurofeedback Treatment Response in ADHD Using EEG Functional Connectivity and Genetic Algorithm-Driven Channel Selection.
  In this article, we present a computational framework for predicting treatment response to neurofeedback (NF) among patients with Attention-Deficit/Hyperactivity Disorder (ADHD). The proposed framework uses functional brain connectivity analysis of electroence…
  pubmed Li Z, Zhu Z, Li D, Huang S 2026 Jul 24 置信度 0.82
• Chinese expert concern and consensus on applications of artificial intelligence in clinical cancer imaging.
  Artificial intelligence (AI) demonstrates potential throughout the cancer care continuum, with evidence supporting its application in medical imaging for detection, staging, treatment planning, and prognostic evaluation. However, clinical translation is hinder…
  pubmed Wu H, Yin X, Cheng J, Zhang J 等 2026 Jul 24 置信度 0.82
• Graph-Based White Matter Tractometry: Methods, Applications, and the Path to Validation.
  Graph-based white matter tractometry represents bundles as networks, preserving spatial topology that traditional along-tract profiles collapse. This enables the detection of distributed pathology patterns organized across connected regions. The field is at a …
  pubmed Li J, Zhang C, Wan Z, Xie Y 等 2026 Jul 24 置信度 0.82
• Improving clinical reliability of LLM reasoning for depression assessment via structured generation and GRPO.
  ObjectiveDigital mental health screening is increasingly explored through the use of AI systems. Yet, most models provide limited insight into how predictions are derived, restricting clinical trust and patient-centered adoption. We investigate whether Large L…
  pubmed Bao E, Perez A, Parapar J 2026 Jul-Sep 置信度 0.82
• The next century of Academic Medicine: balancing high tech and high touch in the age of artificial intelligence.
  As Academic Medicine marks its centennial, academic medical centers (AMCs) face a defining inflection point driven by the convergence of generative artificial intelligence (AI), machine learning, computational biology, digital health platforms, autonomous syst…
  pubmed Prober CG, Shah NH, Arvin AM 2026 Jul 24 置信度 0.82
• Characterization and Validation of EHR Computable Phenotypes for Long COVID Using Patient-Reported Symptoms: Insights from the Nationwide RECOVER Program.
  Long COVID (LC) remains poorly understood, and there is a critical need for advanced computational tools to better identify and characterize patients. In this study, we use summarized symptom reports by RECOVER-Adult cohort participants linked to EHR data to c…
  pubmed Castro VM, Gainer V, Wattanasin N, Cagan A 等 2026 Jul 24 置信度 0.82
• PathMED: an R toolkit for single-sample molecular scoring and machine learning with omics data.
  Molecular scoring is a popular approach for studying pathway-level functional alterations with omics data. Using molecular scores for tasks such as single-sample molecular characterisation, phenotype prediction or disease stratification has several advantages …
  pubmed Martorell-Marugán J, Ellson I, López-Domínguez R, Jurado-Bascón PP 等 2026 Aug 3 置信度 0.82
• Multimodal deep learning fusion for automatic pain detection in cancer patients.
  Since pain is a multidimensional and subjective experience, pain assessment remains challenging. With advances in artificial intelligence (AI), automatic pain assessment (APA) systems offer a valuable opportunity for objective pain evaluation. However, most ap…
  pubmed Cascella M, Mariani F, Barberio D, Crispo A 等 2026 Jan 1 置信度 0.82
• Toward Child-Centred Artificial Intelligence in Pediatric Emergency Medicine: A Perspective on Clinical Decision Support, Stakeholder Engagement and Education.
  Artificial intelligence (AI) is increasingly recognized as a transformative technology in healthcare, with growing evidence supporting its applicability across time-critical clinical environments. This perspective aims to evaluate the integration of AI and mac…
  pubmed Gasparini L, Gobbi N, Zama D, Lanari M 2026 Jul 8 置信度 0.82
• Utilizing Machine Learning for Diagnostic Assistance of Pediatric Sepsis and Septic Shock in Resource-Limited Settings.
  Sepsis is a leading cause of pediatric mortality worldwide, disproportionately affecting children in low- and middle-income countries (LMICs). However, timely recognition of potential sepsis and access to healthcare resources needed to diagnose pediatric sepsi…
  pubmed Bunch K, Shaima SN, Mamun GMS, Jarabana SG 等 2026 Jul 3 置信度 0.82
• Accelerating Pediatric Oncology Drug Development: Advances in Clinical Pharmacology, Trial Design, Non-Clinical Evidence, and Regulatory Science.
  Pediatric oncology drug development remains uniquely challenging due to the rarity and biological heterogeneity of childhood cancers, ethical considerations in trial conduct, and the limited feasibility of large, randomized studies. Despite these barriers, rec…
  pubmed Wen YF, Wang X, Boyanapalli S, Anderson L 等 2026 Jul 置信度 0.82
• Ensemble Machine Learning for Malaria Diagnosis in Resource-Limited Settings Using Clinical and Demographic Features.
  Sub-Saharan Africa suffers the greatest impact of malaria, with the 2024 Health Organization (WHO )report stating that the region represents 94% of global cases and 95% of deaths. Challenges in malaria elimination stem from weak health systems and limitations …
  pubmed Nyengera P, Takawira HT, Mlambo FF 2026 置信度 0.82
• Introduction to the special issue on ecological perspectives on hearing.
  This special issue explores an ecological perspective to hearing in human and non-human animals. The goal is to understand the relationship between the auditory system and the natural sounds of real-world environments, including animal vocalizations such as bi…
  pubmed Heller LM, Desjonqu��res C, Lorenzi C, Theunissen F 2026 Jul 1 置信度 0.82
• Artificial intelligence for the assessment of diastolic function.
  Assessment of left ventricular diastolic function remains one of the most challenging aspects of echocardiography. Artificial intelligence (AI) has emerged as a transformative tool capable of automating data acquisition, analysis, and interpretation. This revi…
  pubmed Tsang TSM, Yeung DF 2026 Sep 1 置信度 0.82
• Measures matter: assessing childhood maltreatment and emotion dysregulation in a transdiagnostic sample.
  Background: Childhood maltreatment (CM) is a major risk factor for different mental disorders and transdiagnostic mechanisms, including emotion dysregulation. Progress in the field has been constrained by substantial variability in the measurement of CM across…
  pubmed Seitz KI, Schalinski I, Renneberg B, Heinrichs N 等 2026 Dec 置信度 0.82
• Altered Cortical Morphological Brain Networks and Their Diagnostic Classification Utility in Major Depressive Disorder.
  Major depressive disorder (MDD) has been increasingly characterized as a network dysconnectivity syndrome. Although single-subject morphological networks are advantageous in studying the brain connectome, extant research on MDD is limited by either small sampl…
  pubmed Sun X, Shen Y, Chen X, Lu B 等 2026 Aug 1 置信度 0.82
• LLM-Generated Lay-Language Protocols for Molecular Tumor Board Patients: Evaluation of Quality and Clinical Usability.
  Molecular Tumor Boards (MTBs) generate highly technical recommendations. The language used in their protocols is rarely accessible to patients. Lay-language patient protocols could support patient-clinician communication, yet manual production is difficult to …
  pubmed Pakull TMG, Bender N, Benson S, Fleischhauer A 等 2026 Jul 23 置信度 0.82
• The effectiveness of adding on or switching antiseizure medications after the first fails to control focal epilepsy: A systematic review of randomized controlled trials.
  Focal epilepsy constitutes 60-70% of epilepsy, and up to half of patients do not achieve seizure freedom with their first antiseizure medication (ASM). When the first ASM fails, evidence guiding whether to switch or add-on another ASM and which ASMs to use is …
  pubmed Egesa IJ, Mbizvo G, Maden M, Spain T 等 2026 Jul 24 置信度 0.82
• Machine learning-based models for predicting the efficacy and safety of recombinant human interleukin-11 in the treatment of cancer therapy-induced thrombocytopenia: exploration and preliminary validation from a multicenter retrospective study.
  Cancer therapy-induced thrombocytopenia (CTIT) is a common hematologic toxicity associated with anti-tumor treatment. Recombinant human interleukin-11 (rhIL-11), as a thrombopoietic agent, is widely used in clinical practice. However, its efficacy and safety e…
  pubmed Wen Y, Xia J, Dong Y, Liu Z 等 2026 置信度 0.82
• Artificial Intelligence-Driven Multimodal Prediction of 10-Year Incident Glaucoma Integrating Genetic and Deep Learning-Derived Imaging Features.
  Glaucoma is the leading cause of irreversible blindness worldwide. It often remains asymptomatic until advanced stages. Hence, accurate prediction of glaucoma is crucial for timely intervention to prevent vision loss.
  pubmed Wu F, Gao XR 2026 Aug 置信度 0.82
• Can Machine Learning Reduce Unnecessary Surgeries? A Retrospective Analysis Using Threshold Optimization to Prevent Negative Appendectomies in Adults.
  To develop and validate machine learning models using routinely available clinical and laboratory data in adults with highly suspected acute appendicitis and to assess their potential to reduce negative appendectomies.
  pubmed Males I, Kumric M, Boban Z, Vrdoljak J 等 2026 Apr 28 置信度 0.82
• Decoding early lung adenocarcinoma progression by single-cell and spatial transcriptomics reveals a CMA-related prognostic signature.
  Lung adenocarcinoma (LUAD) progression from adenocarcinoma in situ (AIS) to minimally invasive adenocarcinoma (MIA) and invasive adenocarcinoma (IAC) is accompanied by molecular heterogeneity and tumor microenvironment remodeling. Chaperone-mediated autophagy …
  pubmed Wang J, Wang W, Li S, Ji X 2026 置信度 0.82
• Uncovering the pivotal role of MYO6 in myocardial infarction: a multimodally validated diagnostic biomarker and immunotherapeutic target.
  Myocardial infarction (MI) remains a leading cause of cardiovascular mortality worldwide, underscoring the need for improved diagnostic and therapeutic strategies. Despite recent in clinical management, delayed diagnosis and complications such as adverse myoca…
  pubmed Wang J, Lei Z, Chen D, Chen Z 等 2026 置信度 0.82
• Study on the Current Status of Supportive Care Needs of Elderly Breast Cancer Patients and Influencing Factors.
  This study investigated the current status and key influencing factors of supportive care needs among elderly breast cancer patients, with a focus on identifying critical determinants through a survey and advanced machine learning techniques.
  pubmed Tian W, Gao J, Wei T, Zhang Y 等 2026 置信度 0.82
• Synergistic Profiling of Programmed Cell Death and Immune Responses Identifies a Novel Prognostic Index for Cervical Cancer.
  Cervical cancer (CC) is one of the leading malignancies impacting women worldwide, with a large number of cases occurring in developing countries. However, there is a need for optimal predictive models that can precisely forecast the prognosis and guide treatm…
  pubmed Kiruba B, Sundararajan V 2026 Jul 21 置信度 0.82
• Machine learning early risk assessment model for acute kidney injury in critically ill children: a retrospective cohort study.
  Acute kidney injury (AKI) is a common severe complication in intensive care unit (ICU). However, an early risk assessment model that can accurately and promptly predict the risk of AKI in critically ill children remains lacking.
  pubmed Xie L, Chen C, Zhang C, Chen L 等 2026 置信度 0.82
• The epistemology of death: psychological autopsy, artificial intelligence, and forensic decision-making in equivocal deaths.
  Traditional post-mortem examinations primarily focus on determining the biological cause of death (causa mortis). However, in equivocal death cases, understanding the intention underlying death may be as important as identifying its physiological mechanism. Ps…
  pubmed Kaya K, Erdem Z, Akpınar Ö, Kaya D 2026 置信度 0.82
• Multiomics and artificial intelligence identify infection associated subtypes and prognostic signatures in hepatocellular carcinoma.
  Hepatocellular carcinoma (HCC) remains a major global health burden with persistently high morbidity and mortality. Dysregulation of the tumor microenvironment (TME) associated with chronic hepatitis B virus (HBV)/hepatitis C virus (HCV) infection and inflamma…
  pubmed Wang P, Fang J, Zhao W, Huang Y 2026 Aug 置信度 0.82
• Development and external validation of a composite biomarker-based machine learning model for sarcopenia risk stratification in patients with cardiovascular disease.
  Sarcopenia is common in patients with cardiovascular disease (CVD) and is associated with functional decline and adverse clinical outcomes. However, practical tools for early risk stratification in this population remain limited, particularly those incorporati…
  pubmed Mei P, Ying T, Wu J, Wang H 2026 置信度 0.82
• Artificial intelligence technology in aortic valve disease: a decade of scientometric and narrative review.
  Aortic valve disease, particularly aortic stenosis, poses a growing global health burden with aging populations. Artificial intelligence technology offers promising tools for diagnosis, risk stratification, and prognosis prediction, yet the knowledge structure…
  pubmed Hei P, Ren H, Ma W, Fang W 等 2026 置信度 0.82
• Translational AI in whole-slide image cancer histopathology: state of the art and regulatory-approved solutions.
  With an emphasis on applied evidence, we present an in-depth evaluation of artificial intelligence (AI) in cancer histopathology through the lens of United States Food and Drug Administration (FDA)-approved and European Conformity-marked whole-slide image In V…
  pubmed Matzko RO, Kucukgoz B, Gertner P, Carey C 等 2026 置信度 0.82
• Streamlining eligibility assessment for Alzheimer's disease-modifying therapies: Prediction of MMSE scores using the digital clock and recall.
  The eligibility of anti-amyloid disease-modifying therapies (DMTs) and their integration into clinical practice in some institutions requires a specific range of Mini-Mental State Examination (MMSE) scores. Reliance on this pencil-and-paper psychometric instru…
  pubmed Jannati A, Toro-Serey C, Ciesla M, Chen E 等 2026 置信度 0.82
• Identification of age-specific urinary metabolic biomarkers in Wilson disease using machine learning: a comparative study of ensemble tree models.
  The diagnosis of Wilson disease (WD) is complicated by heterogeneous clinical phenotypes and inadequate performance of routine biomarkers. This study sought to screen age-specific urinary metabolic biomarkers to assist WD diagnosis via ensemble tree-based mach…
  pubmed Huang S, Song Y 2026 Jan 置信度 0.82
• Myo-ODE: continuous-time trajectory reconstruction and risk prediction of high myopia via neural ordinary differential equations.
  The global surge in childhood myopia necessitates robust screening tools for early risk stratification; however, conventional predictive models often struggle with irregular follow-up intervals and fail to capture the continuous nature of refractive developmen…
  pubmed Zhao N, Zheng R, Lu J, Huang Z 等 2026 置信度 0.82
• Enhancing sarcopenia screening in primary care: a machine learning approach using simple physical tests vs. SARC-F in 2,788 community-dwelling older adults.
  SARC-F, a widely used screening tool for sarcopenia, offers high specificity but poor sensitivity (30-50%), leading to substantial missed diagnoses in community settings.
  pubmed Jiang Z, Zhong C, Yin X, Jin Y 等 2026 置信度 0.82
• Machine learning for early screening of influenza A-associated invasive pulmonary aspergillosis in hospitalized patients: a real-world study.
  Influenza A-associated invasive pulmonary aspergillosis (IAPA) is a severe fungal complication with high mortality, while early identification remains difficult because of nonspecific clinical manifestations. This study aimed to develop and validate a machine …
  pubmed Wang Y, Liu C, Cao M, Chen X 等 2026 置信度 0.82
• Prediction of loss of heterozygosity in oral cavity dysplasia through vascular pattern.
  Loss of Heterozygosity (LOH) is a key genetic alteration associated with progression of oral cavity dysplasia to oral squamous cell carcinoma, yet non-invasive methods to predict LOH status are lacking. The aim of this study is to investigate whether vascular …
  pubmed Tartaglia FC, Rossi G, Mainardi L, Wang H 等 2026 置信度 0.82
• Heart Failure sub-phenotyping and in-hospital and 28-day mortality prediction based on mean arterial pressure trajectory modeling.
  Acute decompensated heart failure patients follow a broad range of clinical pathways during hospitalization. Efficient patient sub-phenotyping based on early in-hospital trajectories, particularly when paired with clinical measurements, may inform optimal trea…
  pubmed Gelbach PE, Edwards RA, Fukuda Y, Alexander J Jr 2026 Sep 置信度 0.82
• End-to-End Pipeline Integrating Local Small Language Models and Machine Learning for Data Extraction and Stroke Outcome Prediction in Emergency Department.
  Background: A substantial proportion of clinical data is stored in unstructured text, limiting its utility for evidence generation. Small language models (SLMs) can extract information but face hallucination risks and privacy concerns. Locally deployable SLMs …
  pubmed Kim J, Kim JH, Choi A 2026 置信度 0.82
• The Potential of Digital Twins in Stroke Care: A Systematic Review of Current Applications and Future Perspectives.
  Background: Digital twin technology holds promise for personalized stroke care, but current applications remain fragmented. This systematic review investigates how digital twins are currently utilized in the stroke care continuum. Methods: Following PRISMA gui…
  pubmed Nawabi J, Eminovic S, Desser D, Fetscher L 等 2026 置信度 0.82
• Machine learning redevelopment of GRACE, ACEF, and TIMI scores for 6-month mortality.
  In recent years, advancements in our understanding of the pathophysiological mechanisms underlying coronary artery disease (CAD) have introduced new challenges regarding the clinical application of traditional risk scores. While studies suggest that machine le…
  pubmed Han B, Zhu Z, Guo R, Xu J 等 2026 置信度 0.82
• Smart FL: meta-learning for federated blood marrow smear classification.
  Accurate classification of bone marrow cells is crucial for diagnosing hematological disorders, yet integrating machine learning and deep learning models into clinical practice faces hurdles like data privacy and data scarcity. Existing models often lack the a…
  pubmed Ilakiyaselvan N, Sanskar S, Aarthi D, Kalyanasundaram V 2026 置信度 0.82
• Beyond AUC: a clinician's guide to building and trusting prediction models in oncology-a narrative review.
  Prediction models are central to advancing precision oncology, yet many fail to translate into clinical practice due to methodological flaws and inadequate validation. This review provides a practical, clinician-oriented guide to the statistical principles and…
  pubmed Wang X, Dou Y, Wang Y, Sun K 等 2026 置信度 0.82
• Development and validation of a machine learning-based early warning model for bone metastasis in newly diagnosed prostate cancer.
  Bone metastasis (BM) is common in newly diagnosed prostate cancer (PCa), particularly in patients with advanced disease at presentation. However, the indications for bone scintigraphy remain inconsistent and may lead to unnecessary imaging in low-risk patients…
  pubmed Wang L, He W, Zhao C, Lv Q 等 2026 置信度 0.82
• Correction: Uncovering potential molecular biomarkers for cancer-associated secondary lymphedema through integrated analyses of RNA-sequencing, machine learning, and clinical data.
  [This corrects the article DOI: 10.3389/fonc.2026.1760040.].
  pubmed Dong H, Miao J, Liu Z, Sun Y 等 2026 置信度 0.82
• Triptolide targets JUN to reverse cisplatin resistance of ovarian cancer: insights from single-cell transcriptome analysis and machine learning validation.
  Platinum-resistant ovarian cancer (PROC) is a major clinical challenge driven by profound intratumoral heterogeneity. Triptolide (TP) exhibits promising anti-tumor potential, yet its precise mechanisms within PROC remain elusive due to the limitations of tradi…
  pubmed Wang C, Guo J, Ye T, Zhu J 等 2026 置信度 0.82
• CRISPRing through time: How cutting-edge technology is revolutionizing life sciences and medicine.
  Given the plethora of emerging technologies, none have truly captured the minds as CRISPR. From the groundbreaking research, the ultimate battle of the prizes and patents to a number of books, the science of CRISPR continues to be significant in the biomedical…
  pubmed Banik I, Coppé JP 2026 Sep 8 置信度 0.82
• Enhanced prediction of coronary heart disease risk in diabetic patients via Machine learning incorporating multiple inflammatory and metabolic indices: A study with Dual-Cohort validation.
  Coronary heart disease (CHD) remains a leading cause of mortality worldwide, with individuals with diabetes mellitus (DM) facing markedly elevated risk due to complex inflammatory and metabolic disturbances. Emerging composite inflammatory and metabolic indice…
  pubmed Xie P, Ran X, Zhu W, Xie Y 等 2026 Aug 置信度 0.82
• Oral-gut strain sharing after Roux-en-Y gastric bypass: A canonical oral microbiome signature in the gut linked to hepatic and glycemic remodeling.
  Roux-en-Y gastric bypass (RYGB) induces durable weight loss and metabolic improvement, but the role of oral microbiota in shaping postsurgical gut ecology and metabolic outcomes is unclear. We examined whether RYGB promotes transfer and expansion of oral strai…
  pubmed Voermans B, Prange K, Bruin S, Acherman Y 等 2026 置信度 0.82
• The progress in predictive modeling of post-stroke epilepsy.
  Post-stroke epilepsy (PSE) is a significant complication of both ischemic (IS) and hemorrhagic strokes (HS), leading to increased morbidity and reduced quality of life. Accurate prediction of PSE risk is essential for early intervention and tailored management…
  pubmed Chen H, Ge L 2026 置信度 0.82
• Integrating Mendelian randomization, machine learning and retrospective clinical data: an exploratory analysis of the cross-disease association between CHB and PD, with a focus on eosinophil alterations.
  Epidemiological studies on the association between chronic hepatitis B (CHB) and Parkinson's disease (PD) have yielded inconsistent findings, with causality obscured by confounding and limited mechanistic evidence.
  pubmed Ge Y, Cai H, Li Y, Li Y 等 2026 置信度 0.82
• Predictive Modeling of the Need for Tracheostomy after Traumatic Cervical Spinal Cord Injury Using Machine Learning.
  Traumatic cervical spinal cord injury (TCSCI) frequently necessitates mechanical ventilation, and early tracheostomy has been shown to reduce complications in patients requiring prolonged ventilation. This study aimed to develop a machine learning model to pre…
  pubmed Lee EJ, Kwon B, Kim S, Noh SH 2026 置信度 0.82
• Multi-Class and Multi-Level Classification for Common Wound Bacteria Based on Reflectance Hyperspectral Imaging.
  Hyperspectral imaging is an emerging non-destructive technique for rapid bacterial detection. However, existing methods often inadequately exploit spatial-spectral correlations and lack datasets tailored to clinically relevant scenarios. This work presents a s…
  pubmed Wu D, Fu X, Liu W, Yin S 等 2026 Jul 置信度 0.82
• Development of a Machine Learning-Based Model for Classifying Depression Using Physiological and Psychological Indicators.
  This study aimed to develop and evaluate machine learning-based models for classifying depression symptoms using salivary hormone markers (cortisol and dehydroepiandrosterone [DHEA]) and psychological indicators from depression screening devices, and to determ…
  pubmed Jang S, Park J, Shin H, Lee M 等 2026 Jul 置信度 0.82
• Crowdsourcing and machine learning contests in Parkinson's disease research - when do they work?
  ObjectiveTo review the application of crowdsourcing and machine learning contests in Parkinson's disease (PD) research, identify best practices for successful implementation, and highlight future opportunities.MethodsThis paper analyzes the landscape of crowds…
  pubmed Kirsch LC, Hausdorff JM, Dardov VJ 2026 Jul 23 置信度 0.82
• Advancing Antiviral Design: Integrating Natural Products, Computation and Targeted Delivery.
  The COVID-19 pandemic highlighted the role of rapid viral mutation and global connectivity in accelerating viral emergence and spread, emphasising the necessity for expedited and adaptable antiviral drug discovery and development. Despite ongoing efforts to de…
  pubmed Lanrewaju AA, Folami AM, Sabiu S, Swalaha FM 2026 Jul 置信度 0.82
• Early prediction of anastomotic leakage within 24 h after minimally invasive colorectal cancer surgery using postoperative inflammatory markers: development and temporal validation of a machine learning model.
  Early identification of anastomotic leakage (AL) is critical for safe discharge within enhanced recovery pathways. This study developed and prospectively validated a machine learning (ML) model to predict AL using 24-h postoperative inflammatory biomarkers.
  pubmed Martin-Arevalo J, Guimaraes A, Palomo-Lopez I, Moro-Valdezate D 等 2026 Jul 23 置信度 0.82
• Gut Microbiome in Depression with and without REM Sleep Behavior Disorder.
  Major depressive disorder (MDD) is a risk factor for neurodegeneration, yet its heterogeneity makes identifying at-risk subtype challenging. Notably, MDD frequently co-occurs with REM sleep behavior disorder (RBD), a specific prodrome of α-synucleinopath…
  pubmed Yang Y, Li N, Zhou L, Gong S 等 2026 Jul 23 置信度 0.82
• Quantitative correlation of spectroscopic signatures with ligand-protein interactions in anti-cancer drug Afinitor: an integrated experimental-computational study.
  A detailed molecular-level understanding of anticancer drugs is essential for improving therapeutic efficacy and guiding rational drug design. Everolimus (Afinitor), a clinically important inhibitor of the mammalian target of rapamycin (mTOR) pathway, is widel…
  pubmed Ramana PV, Ram R, Bobbili P, Krishna YR 等 2026 Jul 23 置信度 0.82
• [Characteristics of urinary organic acid metabolic profile and screening of key metabolic markers in patients with urolithiasis].
  To systematically compare the differences in urinary organic acid metabolic profiles between patients with urinary calculi and non-calculi individuals, to screen disease-specific characteristic metabolic biomarkers and key signaling pathways, and to elucidate …
  pubmed Qi Z, Bian X, Hu H, Tian C 等 2026 Aug 18 置信度 0.82
• Predicting Malignant Transformation in Oral Epithelial Dysplasia: A Systematic Comparison of Artificial Intelligence-Based Risk Models and Pathologist-Based Microscopy.
  Risk prediction models (RPMs) based on histopathological analysis of oral epithelial dysplasia (OED) are increasingly used to stratify patients with oral potentially malignant disorders (OPMDs) and support personalized management. This systematic review and me…
  pubmed Arantes DCB, Delgado LM, Dos Santos MMPP, Warnakulasuriya S 等 2026 Jul 23 置信度 0.82
• The Value of Deep Learning in Differentiating Thyroid Adenomatoid Nodules on Ultrasound: A Dual-Center Study.
  Follicular neoplasms are difficult to classify by ultrasound, as they often present as thyroid adenomatoid nodules (TANU). Furthermore, fine-needle aspiration cytology (FNAC) exhibits limited accuracy in differentiating the nature of follicular lesions. This s…
  pubmed Cheng S, Liang X, Zeng XT, You ZL 等 2026 Jul 24 置信度 0.82
• A Machine Learning-Based Multimodal Model Integrating Radiomics and Clinical Features for Predicting Interstitial Lung Disease: Development and External Validation.
  To develop and validate a multimodal model for predicting the risk of interstitial lung disease (ILD) by integrating radiomics features with clinical variables using machine learning (ML).
  pubmed Wang Y, Zhang Z, Dai X, Shan B 等 2026 Jul 24 置信度 0.82
• A deep learning model for speech-based prediction of clinical scores in people with Huntington's disease: a longitudinal study with cross-sectional replication.
  Sensitive monitoring tools are needed to track progression in neurodegenerative diseases and assess interventions before overt brain damage occurs. We propose speech as a non-invasive, easily collected biomarker to capture disease-related variation over time. …
  pubmed Le Moine Veillon C, Fraisse S, Lunven M, Fabre A 等 2026 Aug 置信度 0.82
• Machine learning-based prediction of shigellosis in children under five: development and internal validation of a prediction model.
  Shigella remains a major cause of diarrhoea and mortality in children under five in low- and middle-income countries, where laboratory confirmation is often inaccessible and dysentery-based management lacks sensitivity. This study aimed to develop and internal…
  pubmed Al Fidah MF, Islam MR, Faruque A, Nuzhat S 等 2026 Jul 23 置信度 0.82
• Artificial intelligence-based methods and applications in clinical and diagnostic microbiology: Current challenges and future perspectives.
  Microbiology laboratories play a critical role in the diagnosis and management of infectious diseases. However, recent advancements aimed at reducing human workload and minimizing time loss are gaining popularity. Artificial intelligence (AI) technologies, par…
  pubmed Yeni DK, Güven D, Büyük F, Gökmen MC 2026 Sep 置信度 0.82
• Liquid biopsy cell-free RNA-based machine learning enables preoperative risk-stratification of uterine leiomyosarcoma.
  Accurate preoperative distinction between uterine leiomyoma and uterine leiomyosarcoma remains a major clinical challenge. Misclassification can lead to inadvertent dissemination of occult malignancy during minimally invasive procedures, while cautious managem…
  pubmed Stahlschmidt SR, Lago V, Machado-López A, Boldú-Fernández S 等 2026 Jul 24 置信度 0.82
• Comprehensive Multi-omics Approach to Investigate the Association Between Metabolic Syndrome and Pituitary Neuroendocrine Tumor Risk in UK Biobank: A Cohort Study.
  Metabolic syndrome (MetS) is a cluster of metabolic disorders linked to cancer development and progression. The pituitary gland plays a central role in systemic metabolic homeostasis. However, the contribution of metabolic disorders to pituitary neuroendocrine…
  pubmed Lin P, Wang Y, Ye Z, Qiao N 等 2026 Jul 23 置信度 0.82
• Transforming blood-derived episignatures into cell-type-agnostic classifiers: A shortcut to prenatal episignatures.
  DNA methylation (DNAm) episignatures are stable disorder-specific epigenetic patterns that serve as valuable biomarkers for assessing variant pathogenicity and phenotypic outcomes in neurodevelopmental disorders (NDDs). However, episignatures derived from whol…
  pubmed Reko N, Torabi-Marashi A, Kallurkar P, Goodman SJ 等 2026 Aug 6 置信度 0.82
• Benefits of Chain-of-Thought Prompting for Clinical Record Rubric Evaluation in Undergraduate Medical Education: Experimental Evaluation Study With Medical Faculty.
  Large language models in artificial intelligence have been among the tools with a significant and real impact on people's daily lives. In this regard, they serve as an aid in specific fields, such as education, helping educators with cumbersome tasks such as p…
  pubmed Nogales A, Denizon S, Mateos Rodriguez A, Cervera Cordero J 等 2026 Jul 23 置信度 0.82
• Clinical Readiness of Artificial Intelligence Models for MB2 Canal Detection in Maxillary Molars: A Scoping Review.
  The second mesiobuccal (MB2) canal detection in maxillary molars represents a notable challenge in endodontics. This scoping review (SR) attempts to map the existing research on artificial intelligence (AI)-based models in MB2 detection, delineating the curren…
  pubmed Shaiban AS, Alobaid MA, Alqahtani OS, Alroomy R 等 2026 Jul 23 置信度 0.82
• Predictive modeling of labor epidural catheter replacement or conversion to spinal or general anesthesia: a multicenter retrospective cohort study (2017-2024).
  Labor epidural analgesia may be inadequate during labor or for cesarean delivery anesthesia. No prediction model identifies cases of labor epidural analgesia with increased risk for epidural catheter replacement or conversion to spinal or general anesthesia.
  pubmed Berenson DF, Eberhard BE, Kleinlein R, Wheeler NK 等 2026 Jul 8 置信度 0.82
• Identifying treatment-responsive patient subgroups in a neutral clinical trial of Intensive blood pressure reduction in acute intracerebral hemorrhage: A post hoc explainable machine learning analysis.
  The Antihypertensive Treatment of Acute Cerebral Hemorrhage (ATACH-2) trial reported no overall benefit from intensive blood pressure (BP) reduction in intracerebral hemorrhage (ICH), potentially masking benefit in select patient subgroups. We evaluated whethe…
  pubmed Tran AT, Qureshi AI, Wen J, Willey JZ 等 2026 Jul 23 置信度 0.82
• Integrative single-cell and machine learning analysis identifies a tumor doubling time-related prognostic signature and therapeutic targets in head and neck squamous cell carcinoma.
  Head and neck squamous cell carcinoma (HNSCC) exhibits marked molecular heterogeneity and diverse clinical outcomes, partly influenced by HPV status and the tumor immune microenvironment. Although tumor doubling time (TDT) reflects tumor growth kinetics and ha…
  pubmed Zhang M, Zhao Z, Zhu Q, Liang S 等 2026 Sep 置信度 0.82
• Performance of large language models in electrocardiogram interpretation: A comparative study.
  As large language models (LLMs) are increasingly used to interpret medical concerns, rigorous evaluation of their performance on clinically relevant tasks is essential. However, the new state-of-the-art models from OpenAI and Google as of February 2026, have n…
  pubmed Chai GW, Chen SJY, Yang J, Chen XYM 等 2026 Jul 21 置信度 0.82
• Machine learning-based extraction of microstructural parameters from diffusion-weighted imaging starting from realistic in silico cellular substrates: Application in breast and prostate cancer.
  Diffusion-Weighted Magnetic Resonance Imaging (DW-MRI) is a key tool for probing tissue microstructure by measuring water motion. Given the invasiveness and limited sampling of biopsies, Apparent Diffusion Coefficient (ADC), derived from DW-MRI acquisitions, i…
  pubmed Tinelli C, Scotti C, Casaccio F, Zlatic M 等 2026 Oct 置信度 0.82
• IEU-Net: Sequence learning of internal texture and external morphology for sonographic kidney segmentation.
  The global prevalence rate of chronic kidney disease (CKD) is on the rise, posing a significant public health concern. Renal ultrasound is an important assessment tool for clinicians. Using automatic ultrasound kidney segmentation would be helpful for kidney e…
  pubmed Lo CM, Chang YC, Chen YK, Luh H 等 2026 Oct 置信度 0.82
• The application of artificial intelligence in healthcare practice: A mapping review of systematic reviews.
  Artificial intelligence (AI) is rapidly transforming healthcare practice, with growing evidence supporting its use in diagnosis, prognosis, treatment planning, and operational decision-making. The proliferation of systematic reviews in recent years underscores…
  pubmed Andersen A, Huang R, Liu EJ 2026 Jul 18 置信度 0.82
• A Community-in-the-Loop Approach to Smart Home Monitoring for Aging in Place: Mixed Methods Evaluation of a Co-Designed Prototype.
  The population of adults aged 65 and older is rapidly increasing, while the availability of caregivers is declining. Smart homes that provide unobtrusive, continuous monitoring and alerting on clinically relevant changes in daily activity patterns offer a pote…
  pubmed Fritz RL, Nguyen-Truong CKY, Phipps J, Hinderlie EE 等 2026 Jul 23 置信度 0.82
• Strategies for Deploying Large Language Models for Ascertaining Clinical Outcomes and Sites of Metastases From Radiology Impressions in Patients With Cancer.
  To evaluate open-source large language models (LLMs) for extracting cancer-specific phenotypic data, benchmark their performance against GPT4 models, and assess the impact of fine-tuning with training data sizes.
  pubmed Naqvi SAA, Riaz IB, Saeidi A, Parmar M 等 2026 Jul-Sep 置信度 0.82
• Prognostic Significance of Cell-Free DNA Derived 5-Hydroxymethylcytosine Signatures in Newly Diagnosed Multiple Myeloma.
  While survival outcomes in multiple myeloma (MM) have improved with contemporary combination therapies, predicting disease trajectories for individual patients at diagnosis remains a significant challenge. We investigate the prognostic value of a noninvasive b…
  pubmed Zhang Z, Derman B, Wang B, Kowitwanich K 等 2026 Jul 置信度 0.82
• Machine learning on asynchronous clinical pages to predict clinical deterioration.
  Clinical deterioration in hospitalized patients is often preventable, but traditional early warning scores based on structured data are limited by delayed or inconsistent documentation. We developed and evaluated a machine learning pipeline that predicts clini…
  pubmed Arvelo IC, Shipley K, Wright A, Steitz BD 2026 Aug 置信度 0.82
• Integrated network pharmacology and bioinformatics analysis reveals multi-target mechanisms of HeJie Shengfa Decoction against alopecia areata.
  Alopecia areata (AA) is a common non-scarring autoimmune disease with a complex pathogenesis, high recurrence rates, and difficulty in achieving a cure. Recent years have seen an increasing focus on both clinical and basic research regarding AA. Hejie Shengfa …
  pubmed Zhao L, Mi H, Diao Z, Tiemuer A 等 2026 置信度 0.82
• Demographics and obesity using a machine learning approach: Iranian National Obesity Registry (IRNOR).
  Obesity and overweight represent significant global health problems. The prevalence of obesity is increasing rapidly in developing countries and is involved in the etiology of cardiovascular disease, diabetes mellitus, and several cancers. In this study, we ai…
  pubmed Nosrati M, Abdollahpour N, Tousi M, Shahabi F 等 2026 置信度 0.82
• Subtyping and risk model construction based on taurine metabolism-related genes for predicting prognosis and immune response in lung adenocarcinoma.
  Lung adenocarcinoma (LUAD) remains a major cause of cancer-related deaths worldwide. While taurine has been shown to suppress tumor growth in laboratory models, its relationship with LUAD patient survival remains unclear. This study constructs a taurine metabo…
  pubmed Wu L, Li M, Zhang J 2026 Jan 置信度 0.82
• Precision Nursing Device Management and Artificial Intelligence-Integrated Early Warning Systems for Central Nervous System Infections in the Neurocritical Care Unit: A Scoping Review.
  Central nervous system (CNS) infections and clinically overlapping neuroinflammatory conditions in the neurocritical care unit (neuro-ICU) are associated with profound mortality and prolonged clinical burdens. Invasive neuromonitoring devices, particularly ext…
  pubmed Zhou Y, Xie H, Hu M, Luo G 2026 Jun 置信度 0.82
• Plasma Lipidomic Signatures Across the Healthy-Pre-COPD-COPD Continuum Identified by Machine Learning.
  Chronic obstructive pulmonary disease (COPD) imposes a substantial global burden, and Pre-COPD is regarded as an early, high-risk window that comprises distinct phenotypes, including small airway dysfunction (SAD), emphysema, and preserved ratio impaired spiro…
  pubmed Xing Y, Yu G, Tian Q, Zhang T 等 2026 置信度 0.82
• An evaluation of first-year medical students' perspectives on hands-on learning of living anatomy using ultrasonography in anatomy.
  Cadaveric dissection has been the gold standard teaching tool and often medical students find it challenging to visualize the functioning human. Point-of-care ultrasound is the future stethoscope and hence, the study aimed to validate students' perceptions on …
  pubmed Shanthi Prabahar P, Sam F, Jacob J, Kulathu Mathew JK 等 2026 Jul-Aug 置信度 0.82
• Prognostic value of the atherogenic index of plasma for early-stage diabetic kidney disease in type 2 diabetes: a retrospective cohort study using supervised machine learning.
  Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease (ESRD). Its insidious onset means that once it progresses to the stage of heavy proteinuria or significant decline in renal function, treatment difficulty and burden increase dramati…
  pubmed Wang Y, Chen H 2026 置信度 0.82
• A prediction model for urological tumor metastasis using liquid biopsy-derived biomarkers.
  To construct and validate a prediction model for tumor metastasis in patients with urological tumors based on liquid biopsy biomarkers and clinical characteristics, to facilitate early clinical identification of metastasis risk and formulation of individualize…
  pubmed Qu J, Zhang J, Huang X 2026 置信度 0.82
• Identification of AICD-associated transcriptomic markers in major depressive disorder.
  Major Depressive Disorder (MDD) is a complex mental disorder with unclear molecular mechanisms. This study aimed to identify key genes associated with ATP-induced cell death (AICD) in MDD and elucidate their roles in disease pathogenesis.
  pubmed Xiong S, Liao L, Chen M, Peng R 等 2026 置信度 0.82
• Health Disparities in Orthobiologics: Factors Influencing Access to Platelet-Rich Plasma for Knee Osteoarthritis.
  Platelet-rich plasma (PRP) is an emerging therapy that demonstrates potential benefits for knee osteoarthritis (OA); however, the accessibility of PRP remains limited, in part, because its use is not covered by insurance.
  pubmed Addani M, Arthurs J, Haque S, Geamanu A 等 2026 Jul 置信度 0.82
• Structured-to-text ClinicalBERT embeddings with random Forest for heart disease prediction: a proof-of-concept study on the UCI Statlog dataset.
  Heart disease remains one of the leading causes of mortality worldwide, highlighting the need for accurate and early risk prediction systems. Traditional machine learning approaches for cardiovascular disease prediction primarily rely on structured clinical at…
  pubmed Priyadharshini U, Vijayan R 2026 置信度 0.82